Disaster Information Perception and Communication Technology and Equipment for Emergency Rescue in Urban Underground Space

Objectives Urban underground spaces are critical components of modern urban infrastructure but they are highly vulnerable during natural disasters due to the blind, narrow, chaotic, and dangerous conditions. These characteristics cause significant challenges to emergency rescue operations, including difficulties in acquiring accurate disaster information and maintaining reliable communication. This study aims to develop an integrated framework for disaster information perception and communication technology and equipment, specifically tailored for emergency rescue in urban underground spaces, to enhance rescue efficiency and effectiveness.

Methods The proposed framework is guided by the principles of intelligent, lightweight, standardized, and systematic and comprises three core components. The first component is multi-state disaster information perception and autonomous operation technology. It includes 3D terrain mapping based on simultaneous localization and mapping (SLAM) to reconstruct disaster scenes, micro-assembled sensors for detecting temperature, humidity, and toxic gases, and social information fusion to provide a comprehensive understanding of the disaster situation. The second one is multi-network collaborative emergency communication network technology. It involves point-to-point communication using adaptive frequency variation and beamforming algorithms to enhance signal transmission, combined with a dynamic network switching strategy to ensure reliable communication in challenging underground environments. The third one is intelligent service platform system. This system integrates real-time data fusion and visualization from multiple sources and provides decision support through algorithms for path planning, resource allocation, and risk assessment.

Results The proposed framework is validated in various underground scenarios, showing significant improvements in disaster information perception and communication capabilities. The first component is disaster information perception. The SLAM-based system achieved high-resolution reconstruction of underground environments and identified key features such as stairs and slopes. Micro-assembled sensors provided accurate environmental data, and the social information fusion component enhanced situational awareness through multi-source data integration. The second one is autonomous operation. The unmanned vehicle was characterized by wheel-track-leg and demonstrated adaptability to complex terrains with vertical obstacle crossing capability up to 25 cm and a climbing ability of 35°. The carbon fiber cage-protected drone provided stable aerial surveillance in confined spaces. The third one is communication network. It ensured reliable communication over 1.2 km distances, dynamically adapting to environmental changes. Point-to-point communication showed robust performance with high data rate and low latency. The last one is intelligent service platform system. It provided real-time data integration and visualization, supporting decision-making through actionable insights based on real-time analysis.

Conclusions The proposed framework addresses the unique challenges faced by urban underground space emergency rescue through systematic and intelligent design, enhancing the efficiency and safety of rescue operations. Future work can focus on optimizing the system to adapt to more complex and diverse environments, thereby further improving its capabilities.